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从高光谱海洋反射率中量化的浮游植物群落与基于色素的群落相对应。

Phytoplankton communities quantified from hyperspectral ocean reflectance correspond to pigment-based communities.

作者信息

Kramer Sasha J, Maritorena Stéphane, Cetinić Ivona, Jeremy Werdell P, Siegel David A

出版信息

Opt Express. 2024 Sep 23;32(20):34482-34491. doi: 10.1364/OE.529906.

DOI:10.1364/OE.529906
PMID:40514827
Abstract

Community detection analysis is a powerful tool to separate groups of samples that are similar based on their composition. Here, we use a paired global dataset of in-water hyperspectral remote sensing reflectance (Rrs) spectra and high-performance liquid chromatography (HPLC) pigment concentrations to investigate the similarity in phytoplankton composition of the communities detected from each method. Samples were separated into optical communities using network-based community detection analysis applied to the Rrs residual (δRrs), which is calculated by subtracting a modeled hyperspectral Rrs spectrum from a measured hyperspectral Rrs spectrum. The δRrs spectrum accentuates short spectral scale features (<=10 nm) that should be related to phytoplankton pigment composition metricsTo test whether these optical communities correspond to phytoplankton communities, we also used network-based community detection analysis to separate HPLC pigment-based communities from twelve accessory pigment ratios to total chlorophyll-a. Our results demonstrate that three distinct phytoplankton communities can be separated from both hyperspectral Rrs data and HPLC pigment data and that a majority of these samples (74%) were assigned to the same communities. Differences in community assignment were also identified and potential sources for discrepancies were discussed. Importantly, the optical communities assigned here offer a new tool for assessing phytoplankton community composition on global scales using hyperspectral Rrs observations, such as those provided by the Ocean Color Instrument (OCI) on NASA's new Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite.

摘要

群落检测分析是一种强大的工具,可用于根据样本组成将相似的样本组区分开来。在此,我们使用一个配对的全球数据集,该数据集包含水中高光谱遥感反射率(Rrs)光谱和高效液相色谱(HPLC)色素浓度,以研究通过每种方法检测到的群落中浮游植物组成的相似性。使用基于网络的群落检测分析,将样本根据Rrs残差(δRrs)分为光学群落,δRrs是通过从实测高光谱Rrs光谱中减去模拟的高光谱Rrs光谱计算得出的。δRrs光谱突出了与浮游植物色素组成指标相关的短光谱尺度特征(<=10 nm)。为了测试这些光学群落是否与浮游植物群落相对应,我们还使用基于网络的群落检测分析,从十二种辅助色素与总叶绿素a的比率中分离出基于HPLC色素的群落。我们的结果表明,可以从高光谱Rrs数据和HPLC色素数据中分离出三个不同的浮游植物群落,并且这些样本中的大多数(74%)被分配到相同的群落。还确定了群落分配的差异,并讨论了差异的潜在来源。重要的是,此处分配的光学群落为使用高光谱Rrs观测在全球尺度上评估浮游植物群落组成提供了一种新工具,例如美国国家航空航天局新的浮游生物、气溶胶、云、海洋生态系统(PACE)卫星上搭载的海洋颜色仪器(OCI)所提供的观测数据。

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